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在低信噪比条件下检测出直接序列扩频(DSSS)信号后,要恢复出原始信息,估计出扩频码序列是非常关键的,因此有必要研究DSSS信号的扩频码序列估计算法。提出了一种基于改进的协方差矩阵迭代算法应用于估计扩频码序列。理论分析和计算机仿真实验都表明了该算法能在低信噪比下估计出扩频码序列,与其他一些扩频码序列估计算法如基于投影子空间的算法、基于神经网络的算法相比,具有运算量更小等优势。
After detecting direct sequence spread spectrum (DSSS) signal under low signal-to-noise ratio (SNR) conditions, it is very important to recover the original information and estimate the spreading code sequence. Therefore, it is necessary to study the DSSS sequence estimation algorithm. An iterative algorithm based on improved covariance matrix is proposed to estimate the spreading code sequence. Both theoretical analysis and computer simulation show that this algorithm can estimate the spreading code sequence at low signal-to-noise ratio. Compared with some other algorithms, such as projection subspace-based algorithm and neural network-based algorithm, With a smaller amount of computing and other advantages.